The lattice Boltzmann method （LBM） is used to examine free convection of nanofluids. The space between the cold outer square and heated inner circular cylinders is filled with water including various kinds of nanopa...The lattice Boltzmann method （LBM） is used to examine free convection of nanofluids. The space between the cold outer square and heated inner circular cylinders is filled with water including various kinds of nanoparticles： TiO2, Ag, Cu, and A1203. The Brinkman and Maxwell-Garnetts models are used to simulate the viscosity and the effective thermal conductivity of nanofluids, respectively. Results from the performed numerical analysis show good agreement with those obtained from other numerical meth- ods. A variety of the Rayleigh number, the nanoparticle volume fraction, and the aspect ratio are examined. According to the results, choosing copper as the nanoparticle leads to obtaining the highest enhancement for this problem. The results also indicate that the maximum value of enhancement occurs at λ =2.5 when Ra = 106 while at A = 1.5 for other Rayleigh numbers.展开更多
To predict the dendrite morphology and microstructure evolution in the solidification of molten metal,numerically,lattice Boltzmann method(LBM)-cellular automata(CA)model has been developed by integrating the LBM to s...To predict the dendrite morphology and microstructure evolution in the solidification of molten metal,numerically,lattice Boltzmann method(LBM)-cellular automata(CA)model has been developed by integrating the LBM to solve the mass transport by diffusion and convection during solidification and the CA to determine the phase transformation with respect to the solid fraction based on the local equilibrium theory.It is successfully validated with analytic solutions such as Lipton-Glicksman-Kurz(LGK)model in static melt,and Oseen-Ivantsov solution under the fluid flow conditions in terms of tip radius and velocity of the dendrite growth.The proposed LBM-CA model does not only describe different types of dendrite formations with respect to various solidification conditions such as temperature gradient and growth rate,but also predict the primary dendrite arm spacing(PDAS)and the secondary dendrite arm spacing(SDAS),quantitatively,in directional solidification(DS)experiment with Ni-based superalloy.展开更多
Efficient communication is important to every parallel algorithm. A parallel communication optimization is introduced into lattice Boltzmann method （LBM）. It relies on a simplified communication strategy which is im...Efficient communication is important to every parallel algorithm. A parallel communication optimization is introduced into lattice Boltzmann method （LBM）. It relies on a simplified communication strategy which is implemented by least square method. After testing the improved algorithm on parallel platform, the experimental results show that compared with normal parallel lattice Boltzmann algorithm, it provides better stability, higher performance while maintaining the same accuracy.展开更多
文摘The lattice Boltzmann method （LBM） is used to examine free convection of nanofluids. The space between the cold outer square and heated inner circular cylinders is filled with water including various kinds of nanoparticles： TiO2, Ag, Cu, and A1203. The Brinkman and Maxwell-Garnetts models are used to simulate the viscosity and the effective thermal conductivity of nanofluids, respectively. Results from the performed numerical analysis show good agreement with those obtained from other numerical meth- ods. A variety of the Rayleigh number, the nanoparticle volume fraction, and the aspect ratio are examined. According to the results, choosing copper as the nanoparticle leads to obtaining the highest enhancement for this problem. The results also indicate that the maximum value of enhancement occurs at λ =2.5 when Ra = 106 while at A = 1.5 for other Rayleigh numbers.
基金financially supported by the Ministry of Trade,Industry,and Energy(MOTIE),Korea,under the“Digital manufacturing platform(Digi Ma P)”(reference number N0002598)supervised by the Korea Institute for Advancement of Technology(KIAT)supported by the National Research Foundation of Korea(NRF)grant funded by the Korean government(2019R1A2C4070160)。
文摘To predict the dendrite morphology and microstructure evolution in the solidification of molten metal,numerically,lattice Boltzmann method(LBM)-cellular automata(CA)model has been developed by integrating the LBM to solve the mass transport by diffusion and convection during solidification and the CA to determine the phase transformation with respect to the solid fraction based on the local equilibrium theory.It is successfully validated with analytic solutions such as Lipton-Glicksman-Kurz(LGK)model in static melt,and Oseen-Ivantsov solution under the fluid flow conditions in terms of tip radius and velocity of the dendrite growth.The proposed LBM-CA model does not only describe different types of dendrite formations with respect to various solidification conditions such as temperature gradient and growth rate,but also predict the primary dendrite arm spacing(PDAS)and the secondary dendrite arm spacing(SDAS),quantitatively,in directional solidification(DS)experiment with Ni-based superalloy.
基金Project supported by the National Natural Science Foundation of China(Grant No.11002086)the Shanghai Leading Academic Discipline Project(Grant No.J50103)
文摘Efficient communication is important to every parallel algorithm. A parallel communication optimization is introduced into lattice Boltzmann method （LBM）. It relies on a simplified communication strategy which is implemented by least square method. After testing the improved algorithm on parallel platform, the experimental results show that compared with normal parallel lattice Boltzmann algorithm, it provides better stability, higher performance while maintaining the same accuracy.
